1. Field of the Invention
The present invention relates to a digital watermark embedding apparatus and a digital watermark embedding method for embedding watermark information into a content such as digital still image data, moving image data, voice data or music data, and a digital watermark detecting apparatus and a digital watermark detecting method for detecting watermark information from a content.
2. Description of the Related Art
Digital watermarking is a technique for embedding information such as discrimination information on the copyright owner or user of a content such as a digital still image, moving image, voice or music, ownership information on the copyright owner, content using conditions, secret information necessary to use the content and/or copy control information (which information is referred to as watermark information) into the content so as to make it difficult to recognize the information, detecting the information later at need from the content, thereby protecting the copyright of the content including the controlling the use of the content and the controlling the copying of the content and promoting the secondary use of the content.
If the digital watermarking is intended to prevent the illegal use of a digital book, it is necessary for the digital watermarking to have robustness for preventing watermark information from being lost or falsified by various operations or intentional attacks normally considered to be applied to the digital book. Depending on a digital watermarking applied field, even if a content which has been converted into an analog signal is digitalized again, it is desirable not to lose the watermark information. This is exemplified by embedding, as watermark information, copy control information into a content. As another example, if ownership information is embedded into a still image and the still image is printed out (or sometimes copied) and digitalized by a scanner (D-A-D conversion), then it is desirable not to lose the watermark information.
D-A-D conversion is considered to cause a geometrical distortion to an image as shown in FIG. 1. As a software simulating and recreating such a geometrical distortion, there is known StirMark. A StirMark attack employing this simulation software for image data into which digital watermark information is embedded changes the positions of pixels. Therefore, depending on a digital watermarking system or type, the positions of pixels into which the watermark information is embedded cannot be disadvantageously, accurately recognized during the detection thereof and the watermark information cannot be disadvantageously, accurately read.
In case of digital watermarking in a frequency region, frequency components do not greatly change as long as a geometrical distortion to an image is small and robustness against the StirMark attack is considered to be relatively high. However, as indicated by the change of a dotted line to a solid line shown in FIG. 2, if a geometrical distortion is large or the position of a block into which watermark information is embedded is greatly moved because an image is large in size despite a small distortion, it is difficult to ensure accurate detection.
On the other hand, in case of digital watermarking in a space region, the multiplication of pseudo-random numbers and the superimposition of mask patterns are performed for each pixel. Therefore, if the positions of pixels are moved by a StirMark attack, it is necessary to strictly synchronize the pixel positions (those during embedding with those during detection) by some method; otherwise, it is difficult to ensure accurate detection.
The geometrical distortion is roughly divided into two distortions, a global distortion and a local distortion.
Here, the global distortion means a distortion expressed by parameters independent of positions and the local distortion means a distortion expressed by the parameters which are locally different. The local distortion does not mean that a distortion is limited to a local region. Namely, a global distortion corresponds to a special case of the local distortion.
The global distortion is the scaling, rotation and translation of an entire image and can be expressed by an Affine transformation. The Affine transformation is expressed using six parameters as shown in the next formula:
                              (                                                                      x                  ′                                                                                                      y                  ′                                                              )                =                                            (                                                                                          a                      11                                                                                                  a                      12                                                                                                                                  a                      21                                                                                                  a                      22                                                                                  )                        ⁢                          (                                                                    x                                                                                        y                                                              )                                +                      (                                                                                b                    1                                                                                                                    b                    2                                                                        )                                              (        1        )            
On the other hand, the local distortion is ordinary two-dimensional coordinate transformation as shown in the following formula, where f and g are arbitrary functions:
                              (                                                                      x                  ′                                                                                                      y                  ′                                                              )                =                  (                                                                      f                  ⁡                                      (                                          x                      ,                      y                                        )                                                                                                                        g                  ⁡                                      (                                          x                      ,                      y                                        )                                                                                )                                    (        2        )            
FIG. 3A shows that a rectangle is locally distorted and FIG. 3B shows a local distortion to the rectangle is approximated to an affine transformation for each patch.
Conventionally, some methods for synchronizing pixel positions for a global distortion employs an original image and others do not employ the original image. If an original image is employed, a global transformation is manually performed so as to coincide a detection target image with the original image or a transformation having a highest correlation value is searched by the correlation of pixel values between the images.
There have been proposed many synchronization methods for the digital watermarking system while an original image is not used during detection. It is, therefore, necessary to restore the synchronization of the original image with the detection target image without using the original image. Such synchronization methods are roughly divided into the following three methods (see, for example, Document (1) Kutter Martin, “Towards Affine Invariant Image Watermarking Schemes,” Watermarking Workshop, 1999.)
(1) Template Based Watermarking
A method for embedding a signal (template) for recognizing an image distortion in a frequency region or a space region is referred to as “template watermarking” (see, for example, Document (2) Bender, W., D. Gruhl, N. Morimoto and A. Lu, “Techniques for data hiding,” IBM Systems Journal, 35, 3&4, 313-336, 1996. Document (3) Fleet, David J. and David J. Heeger, “Embedding Invisible Information in Color Images,” ICCP'97, 532-535, 1997. Document (4) Rhoads, Geoffrey B. “Steganography methods employing embedded calibration data,” U.S. Pat. No. 5,636,292, 1997. Document (5) Pereira, Shelby and Thierry Pun, “Fast Robust Template Matching for Affine Resistant Image Watermarking,” The Third Workshop on Information Hiding, 207-218, 1999). The disadvantage of this method is that it is difficult to maintain robustness while suppressing image degradation caused by the template.
(2) Invariant Watermarking
A method for embedding digital watermark information into a region invariant to a geometrical distortion is referred to as “invariant watermarking” (see, for example, Document (6) Ó Ruanaidh, Joseph J. K. and Thierry Pun, “Rotation, scale and transformation invariant digital image watermarking,” Proceedings of ICIP'97, 536-539, 1997. Document (7) Ó Ruanaidh, Joseph J. K. and Thierry Pun, “Rotation, scale and transformation invariant spread spectrum digital image watermarking,” Signal Processing, 66, 303-317, 1998.). This method is effective only to a uniform scale transformation and rotation and not invariant to a transformation for transforming an aspect ratio.
(3) Self-Reference Watermarking
A method for employing digital watermark information itself as a template is referred to as “self-reference watermarking” (see, for example, Document (8) Kutter, M., F. Jordan and F. Bossen, “Digital signature of color images using amplitude modulation,” Proc. of SPIE storage and retrieval for image and video database, 3022-5, 518-526, February 1997; Journal of Electronic Imaging, 7, 2, 326-332, April 1998). According to this method, a reference point is defined in an image, digital watermark information having a preset value is embedded into the reference point, and the reference point is obtained by full retrieval and then other watermark information is extracted during detection. With this method, if only rotation, translation or scaling is performed, detection can be completed in a relatively short time. However, if a retrieval space becomes wide, calculation cost is excessively pushed up. It is, therefore, difficult to apply this method to a local distortion requiring a wider retrieval space.
As a development of this self-reference watermarking method, there is known a method for embedding the same watermark information into horizontally shifted positions and vertically shifted positions a plurality of times and employing the watermark information as a correction signal (see, for example, Document (9) Kutter, M, “Watermarking resisting to translation, rotation, and scaling,” Proceeding of SPIE International Symposium on Voice, Video, and Data Communications, 1998).
Further, there is known another self-reference watermarking method for limiting a geometrical distortion to translation and cut, obtaining a translation quantity from the phase of a Fourier transform coefficient for a digital watermark pattern to thereby reduce retrieval cost (see, for example, Document (10) Takao Nakamura, Hiroshi Ogawa, Atsuki Tomioka and Yohichi Takashima, “A scheme for improving digital watermarking translation and cut resistance,” SCIS'99, 193-198, 1999.).
Additionally, there is known yet another self-reference watermarking method for dividing an image into small blocks and approximating an image distortion to a block translation (see, for example, Document (1)).
The above-stated three improved methods relate to a global distortion. If applied to a local distortion, retrieval cost is disadvantageously pushed up and these improvements are not effective to the local distortion.
As stated above, according to the conventional watermarking, watermark information is lost or falsified by a geometrical distortion such as D-A-D conversion or StirMark attack, with the result that the embedded watermark information such as copy control information and/or ownership information may not be possibly able to be detected. As for robustness against a global distortion out of a geometrical distortion, there have been conventionally proposed some techniques. However, these techniques are not effective for a local distortion such as a StirMark attack or D-A-D conversion.
Further, if measures against a global distortion are forced to be applied to a local distortion, it is feared that considerably long processing time is required.
Besides, if a local distortion becomes large, the measures against the global distortion becomes ineffective.